ROCKWAVE AI - determines the root cause of the malfunction of your filling line

We help production managers of filling and packaging machines to eliminate constantly occurring timestealers by means of a unique algorithm that predicts the behavior of timestealers in order to promptly increase the output of the line and thus avoid profit-reducing production stoppages.

The problem

During ongoing production in discrete manufacturing, timestealers repeatedly cause machine malfunctions that can propagate to the lead machine. In the worst case, the production of the entire line is stopped by an upstream or downstream machine. The following questions always arise:

• Which machine causes the most line stoppages

• How long does the production stand still due to unplanned malfunctions

• How can I reduce production downtimes

The production manager encounters problems in determining the root cause, because the machine causing the malfunction cannot be identified right away. In addition, all machines are subject to certain control and buffer behaviors. Under certain circumstances, malfunctions that occur due to existing downtimes do not reach the master machine. On the other hand, many small, briefly occurring faults can affect the lead machine despite the buffer time that has been designed. As a result, these also lead to a deterioration in plant output.

It is almost impossible to analyze this machine data and derive measures, because the evaluation of the data takes too much time.

The solution

ROCKWAVE AI is a unique algorithm developed from years of experience in the process area of the filling and packaging industry. As experts, we are very familiar with the problem, and have already used ROCKWAVE AI to continuously increase line output at a world leader in the beverage industry!

The way ROCKWAVE AI works differs from other software companies that use digital twins to elaborately simulate behavior. We go one step further - our application measures and evaluates in near real-time all relevant data streams of the machines in a plant using artificial intelligence. These data streams are evaluated in an algorithm and ROCKWAVE AI informs the user in time to initiate measures to improve the plant.

• Identification of the main source of disturbances in complex interlinked plants

• Monitoring of sneaking behavior changes on machines

• Notification of behavioral changes of machines via e-mail

• Monitoring of whether improvement measures are effective

The results

ROCKWAVE AI enables up to 50% reduction in production downtime caused by upstream or downstream machine faults.

The application provides immediate results that do not require time-consuming analysis and interpretation.

Monitoring and evaluating the behavior of each machine is possible without complex configuration, even when changes are made to machines.

ROCKWAVE AI can be integrated with any IIOT platform or MES solution.

EXPERIENCE FROM COUNTLESS SIMULATION PROJECTS IN REAL PLANTS PACKED INTO A UNIQUE ALGORITHM - ROCKWAVE AI